from __future__ import annotations

from typing import Dict

from ...configuration_utils import PretrainedConfig


_snake_case								=    {
    '''susnato/ernie-m-base_pytorch''': '''https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json''',
    '''susnato/ernie-m-large_pytorch''': '''https://huggingface.co/susnato/ernie-m-large_pytorch/blob/main/config.json''',
}




class        _snake_case    (    _lowercase					):
					lowerCamelCase__:		Dict	=  "ernie_m"
					lowerCamelCase__:		int	=  {"dropout": "classifier_dropout", "num_classes": "num_labels"}
					def __init__(	self:					int						,	__lowerCamelCase:					int = 25_00_02						,	__lowerCamelCase:					List[str] = 7_68						,	__lowerCamelCase:					Dict = 12						,	__lowerCamelCase:					int = 12						,	__lowerCamelCase:					List[Any] = 30_72						,	__lowerCamelCase:					List[Any] = "gelu"						,	__lowerCamelCase:					List[Any] = 0.1						,	__lowerCamelCase:					Any = 0.1						,	__lowerCamelCase:					List[str] = 5_14						,	__lowerCamelCase:					List[Any] = 0.02						,	__lowerCamelCase:					str = 1						,	__lowerCamelCase:					Optional[int] = 1e-05						,	__lowerCamelCase:					Dict=None						,	__lowerCamelCase:					List[str]=False						,	__lowerCamelCase:					int=0.0						,	**__lowerCamelCase:					int						,	)     ->					Tuple:
												super().__init__(pad_token_id=__lowerCamelCase						,	**__lowerCamelCase  )
												__UpperCAmelCase    :      Any       = vocab_size
												__UpperCAmelCase    :      List[Any]       = hidden_size
												__UpperCAmelCase    :      Any       = num_hidden_layers
												__UpperCAmelCase    :      Dict       = num_attention_heads
												__UpperCAmelCase    :      Tuple       = intermediate_size
												__UpperCAmelCase    :      Optional[int]       = hidden_act
												__UpperCAmelCase    :      Dict       = hidden_dropout_prob
												__UpperCAmelCase    :      Union[str, Any]       = attention_probs_dropout_prob
												__UpperCAmelCase    :      int       = max_position_embeddings
												__UpperCAmelCase    :      Union[str, Any]       = initializer_range
												__UpperCAmelCase    :      Optional[Any]       = layer_norm_eps
												__UpperCAmelCase    :      Tuple       = classifier_dropout
												__UpperCAmelCase    :      Any       = is_decoder
												__UpperCAmelCase    :      str       = act_dropout










'''simple docstring'''


import math


def     SCREAMING_SNAKE_CASE							(   a_						:				float					,       a_						:				float      ):

  if initial_intensity < 0:
    raise ValueError('The value of intensity cannot be negative'      )
    # handling of negative values of initial intensity
  if angle < 0 or angle > 360:
    raise ValueError('In Malus Law, the angle is in the range 0-360 degrees'      )
    # handling of values out of allowed range
  return initial_intensity * (math.cos(math.radians(a_      )      ) ** 2)


if __name__ == "__main__":
  import doctest

  doctest.testmod(name="malus_law")



